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Reconnaissance of potential alternate water supply sources for the City of Gary, West Virginia

Seven potential sources of water, consisting of free-flowing discharge from abandoned coal mines at six locations and one abandoned flooded underground coal mine air shaft, were sampled for chemical analysis to assess the quality of the groundwater emanating from the seven mine sources. The six free-flowing mine discharge sources were also assessed for discharge by current-meter measurements on two separate occasions. The U.S. Geological Survey assessed these seven sources to provide information to the City of Gary, West Virginia (W. Va.), and the City of Gary’s consulting engineer with groundwater-quality and flow data to allow them to assess the seven sites as potential alternate sources of water for the City of Gary to augment its existing supply. For the six sites where discharge could be measured, discharge ranged from a minimum of 0.082 cubic feet per second (ft 3 /s) to a maximum of 3.685 ft 3 /s. Of the six sites measured, only two, Harmon Branch at Thorpe, W. Va. (USGS site 372201081303501) and the abandoned public-supply water wells near Havaco, W. Va. (USGS site 372358081344601), had discharge in excess of 1.00 ft 3 /s. Discharge from the abandoned public supply wells was 3.685 ft 3 /s on September 20, 2023, and 2.888 ft 3 /s on October 16, 2023, and discharge from Harmon Branch at Thorpe, W. Va., was 1.049 ft 3 /s on September 22, 2023, and 1.038 ft 3 /s on October 17, 2023. Discharge in the abandoned underground mine air shaft (USGS site 372224081340901) could not be assessed, but the air shaft drains an abandoned mine that likely contains water stored in approximately 1.7 square miles (mi 2 ) of abandoned underground coal mines in the Pocahontas No. 3 coal seam, and possibly an additional 0.9 mi 2 of leakage from the overlying Pocahontas No. 4 coal seam. Discharge for the six sites measured for the study was measured during a period between September 20 and October 18, 2023, and corresponded to the 12th to the 15th percentile of flow-duration statistics for the Tug Fork downstream of Elkhorn Creek at Welch, W. Va. streamgage (USGS site 03212750). Water-quality data for the seven sites sampled overall were acceptable with respect to drinking water standards. Of the 203 constituents analyzed, only a few failed to meet applicable U.S. Environmental Protection Agency (EPA) drinking water standards. Iron exceeded the 300 micrograms per liter (μg/L) secondary maximum contaminant level (SMCL) at only 1 of the 7 sites (14.3 percent) sampled. Iron concentrations ranged from a minimum of less than (<) 5.00 μg/L to a maximum of 724 μg/L with a median concentration of 7.62 μg/L. Manganese exceeded the 50.0 μg/L SMCL at 2 of the 7 sites (28.6 percent) sampled. Manganese concentrations ranged from a minimum of 1.93 μg/L to a maximum of 271 μg/L with a median concentration of 4.03 μg/L. No sites sampled exceeded the arsenic maximum contaminant level (MCL) of 10 μg/L. Arsenic concentrations ranged from a minimum of <0.100 μg/L to a maximum of 2.35 μg/L with a median arsenic concentration of 0.200 μg/L. None of the seven sites sampled for selenium for this study exceeded the EPA MCL of 50.0 μg/L. Selenium concentrations ranged from a minimum of <0.050 μg/L to a maximum of 5.26 μg/L with a median concentration of 3.21 μg/L. All seven sites were sampled for volatile organic compounds (VOCs), semivolatile organic compounds (SVOCs), and polychlorinated biphenyls (PCBs), but most had concentrations below the detection limit. Of the 10 PCB compounds analyzed for the seven sites sampled, none contained detectable concentrations of PCBs or Aroclor compounds. Of the 44 SVOCs analyzed at each of the seven sites sampled, only 1 SVOC, acenaphthene, was detected, at a concentration of 0.02 μg/L. Of the 96 VOCs analyzed, from each of the seven sites sampled, only two were found at detectable concentrations. Trichloromethane was detected only at 1 of the 7 (14.3 percent) sites sampled at a concentration of 0.027 μg/L, and benzene was detected at the same site and 3 additional sites (4 of the 7 sites or 57.1 percent of the sites sampled) at concentrations of 0.028, 0.029, 0.021, and 0.035 μg/L, but none exceeded the EPA MCL for benzene of 5.00 μg/L. Total coliform bacteria are ubiquitous in the environment, and their presence only suggests the potential for contamination by near-surface processes. Escherichia coli ( E. coli ) bacteria are derived from either human or animal fecal material and can be an indicator of potential contamination by pathogenic bacteria or viruses. Total coliform bacteria were detected at all 7 sites sampled at concentrations ranging from 17.5 to greater than (>) 2,420 most probable number per 100 mL (MPN/100 mL) of sample, with a median total coliform concentration of 1,553 MPN/100 mL. Escherichia coli bacteria were detected at 4 of the 7 sites sampled at concentrations ranging from <1 to 11.9 MPN/100 mL, with a median E. coli concentration of 5.1 MPN/100 mL.

West Virginia

Relating glassy rind thicknesses to ambient air temperatures at the Lost Jim flow field in the Imuruk Lake volcanic field, Alaska

The Lost Jim flow field, in the Imuruk Lake volcanic field, Alaska, extends west ~34 km from a single vent, crossing subarctic tundra and currently touches several lakes and streams. The weighted mean of five 36Cl cosmogenic exposure ages from the Lost Jim pāhoehoe flow is 7.73 ± 0.37 ka, indicating this eruption occurred substantially after the eruption of the underlying Camille flow, which was emplaced at 39.7 ± 1.3 ka. Paleoclimate records indicate the period when the Lost Jim flow field was emplaced was after deglaciation, and the climate was similar to today. We propose that the emplacement of lava in these cold subarctic conditions can lead to faster cooling of the lava surface compared to lava emplaced in warmer locations such as mid- latitude cold deserts. Glass abundance in the outermost rinds at the Lost Jim flow field was on average 74 % with 6.4 mm thick rims, compared to 60 % with 2.9 mm rims for cold mid-latitude desert samples. We interpret increased glass content as a proxy for rapid cooling likely occurring partly during winter. Glassiness values varied less across vent, margin, and mid-flow locations when compared to the mid-latitude flows suggesting the Lost Jim flow field was broadly impacted by the subarctic climate as opposed to responding to local microclimates. Our results indicate that lava glassiness may be a useful environmental indicator of cooler (in this case subarctic) conditions.

Alaska

Peak streamflow trends in South Dakota and their relation to changes in climate, water years 1921–2020

Peak-flow (flood) frequency analysis is essential to water-resources management applications, including the design of critical infrastructure such as bridges and culverts, and floodplain mapping. Federal guidelines for performing peak-flow flood frequency analyses are presented in a U.S. Geological Survey Techniques and Methods Report known as Bulletin 17C. A basic assumption within Bulletin 17C, which documents the guidelines for determining annual peak streamflow frequency, is that, for basins without major hydrologic alterations (for example, regulation, diversion, and urbanization), statistical properties of the distribution of annual peak streamflows are stationary; that is, the mean, variance, and skew are constant through time. Nonstationarity is a statistical property of a peak-flow series such that the long-term (on the order of decades) distributional properties change one or more times either gradually or abruptly through time. Individual nonstationarities may be attributed to one source such as flow regulation, land-use change, or climate but are often the result of a combination of sources, making detection and attribution of nonstationarities challenging. In response to a growing concern regarding nonstationarity in peak streamflows in the region, the U.S. Geological Survey, in cooperation with the Departments of Transportation of Illinois, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin; the Montana Department of Natural Resources and Conservation; and the North Dakota Department of Water Resources, assessed the potential nonstationarity in peak streamflows in the north-central United States. This chapter characterizes the effects of natural hydroclimatic shifts and potential climate change on annual peak streamflows in the State of South Dakota. Annual peak and daily streamflow as well as model-simulated gridded climatic data were examined for temporal monotonic trends, change points, and other statistical properties indicative of changing climatic and environmental conditions. Changes in annual peak and daily flows were evaluated among 13, 35, and 81 qualifying U.S. Geological Survey streamgages for the 75-, 50-, and 30-year trend periods through water year 2020 (the period from October 1, 2019, to September 30, 2020) in South Dakota, respectively. No qualifying streamgages were in the 100-year trend period in the State. Statistical tests for autocorrelation (independent and identically distributed assumption), monotonic trends, and change points in the median and scale are analyzed to evaluate potential stationarity violations (nonstationarity) for performing at-site peak-flow flood-frequency analysis. The trends are reported using a likelihood approach as an alternative to simply reporting significant trends with an arbitrary p -value cutoff point. A distinct east-west spatial pattern of likely upward and downward monotonic trends and change points, respectively, was detected in 75- and 50-year trend periods, but an inconsistent spatial pattern was detected in the 30-year trend period. Additionally, change points in the median annual peak streamflows were detected in the late 1970s and early 1980s in the western part of the State, but in the east, the change point was more commonly detected in 1992–93. A similar east-west spatial pattern of likely upward and downward trends was detected in the annual peak-flow timing, the day of the year of the annal peak streamflow. In the western part of the State, the annual peak streamflows are arriving earlier, but in the east, the annual peak streamflows are arriving later. A peaks-over-threshold (POT) analysis where, on average, there are two events per year (POT2) and four events per year (POT4) was also used to evaluate changes in the frequency (count) of daily streamflows exceeding the threshold. Similar to detected changes in the annual peak streamflow, an east-west likely upward or downward change corresponding to an increase or decrease, respectively, in the frequency of daily streamflow greater than a POT2 and POT4 threshold was detected. A monthly water-balance model was used to evaluate hydroclimatic variation in annual and seasonal precipitation, snowfall, potential evapotranspiration, and soil moisture storage for all qualifying streamgages in the 75-, 50-, and 30-year trend periods. Detected trends in the annual hydroclimatic metrics for the 75- and 50-year trend periods indicate a spatially consistent statewide increase in precipitation, decrease in snowfall, increase in potential evapotranspiration, and increase in soil moisture storage. Furthermore, detected trends in seasonal precipitation in the 75- and 50-year trend periods highlight a pronounced change in precipitation in winter and later into the summer season, especially in the 50-year trend period in the eastern part of the State. Statewide increases in seasonal soil moisture storage were also detected, highlighting year-round increasing flood magnitudes, particularly in the eastern part of the State. Based on the results of these stationarity tests for the qualifying streamgages in South Dakota among the 75-, 50-, and 30-year trend periods, consistent temporal and spatial patterns of nonstationarity were detected among the 75- and 50-year trend periods. Furthermore, when nonstationarity is detected in daily streamflow, increased streamflow and volume (increasing frequency in POT), as well as potentially bridge scour, may have implications on culvert and highway design in the eastern part of South Dakota. Thus, when performing at-site peak-flow flood-frequency analyses in South Dakota, potential nonstationarities and alternative approaches are important considerations.

South Dakota

Parsimonious high-resolution landslide susceptibility modeling at continental scales

Landslide susceptibility maps are fundamental tools for risk reduction, but the coarse resolution of current continental-scale models is insufficient for local application. Complex relations between topographic and environmental attributes characterizing landslide susceptibility at local scales are not transferrable across areas without landslide data. Existing maps with multiple susceptibility classifications under-represent landslide potential in moderate and gently sloping terrain. We leverage an extensive landslide database ( N = 613,724), a high-resolution digital elevation model (10-m), and high-performance computing resources, to develop a new nationwide susceptibility map for the contiguous United States, Hawaii, Alaska, and Puerto Rico. We calculate four alternative linear and nonlinear thresholds of topographic slope and relief using an objective split-sample calibration. We down-sample our results to a 90-m grid to account for uncertainty in the digital elevation model and landslide position, and evaluate these thresholds' ability to differentiate areas of greater susceptibility. The less conservative nonlinear model optimally balances our priorities of capturing observed landslides (99%) while minimizing area covered by susceptible terrain (43%). Independent evaluation with four statewide landslide inventories ( N = 172,367) reinforces our model selection but highlights spatially variable performance. Therefore, we propose a novel approach to susceptibility classification using the concentration of landslide-prone terrain within each down-sampled grid. While landslides are possible within any cells containing susceptible terrain, those with the highest concentration capture the majority of observed landslides. Our new map characterizes landside susceptibility more consistently than prior models; our transparent classification approach also provides flexibility for accommodating different tolerances in risk reduction measures.

AGU Advances

Seismic tomography 2023

Seismic tomography is the most abundant source of information about the internal structure of the Earth at scales ranging from a few meters to thousands of kilometers. It constrains the properties of active volcanoes, earthquake fault zones, deep reservoirs and storage sites, glaciers and ice sheets, or the entire globe. It contributes to outstanding societal problems related to natural hazards, resource exploration, underground storage, and many more. The recent advances in seismic tomography are being translated to nondestructive testing, medical ultrasound, and helioseismology. Nearly 50 yr after its first successful applications, this article offers a snapshot of modern seismic tomography. Focused on major challenges and particularly promising research directions, it is intended to guide both Earth science professionals and early‐career scientists. The individual contributions by the coauthors provide diverse perspectives on topics that may at first seem disconnected but are closely tied together by a few coherent threads: multiparameter inversion for properties related to dynamic processes, data quality, and geographic coverage, uncertainty quantification that is useful for geologic interpretation, new formulations of tomographic inverse problems that address concrete geologic questions more directly, and the presentation and quantitative comparison of tomographic models. It remains to be seen which of these problems will be considered solved, solved to some extent, or practically unsolvable over the next decade.

Bulletin of the Seismological Society of America

Monitoring changes in Landsat thermal features in urban and non-urban interfaces from 1986 to 2023 in two international urban centers: Implications for climate and global issues

Rapid urbanization is reshaping thermal environments worldwide, with the strongest impacts occurring at the interface between urban and non-urban areas. Impervious surfaces, as key indicators of urban expansion, are critical for monitoring urban growth and assessing surface urban heat island (SUHI) effects. Land use and land cover change (LULCC) provides an essential link between urban dynamics and their environmental and societal consequences. Here, we integrated the U.S. Geological Survey (USGS) Climate Global Issues (CGI) Land Cover Product with Landsat thermal time-series to investigate SUHI evolution in two contrasting metropolitan regions: Wuhan, China, and Brasília, Brazil. Using data spanning 1986–2023, we analyzed the relationships between land cover, Landsat-based land surface temperature (LST), and SUHI intensity, and identified persistent thermal hotspots. Results demonstrate that the land cover data utilized increases the accuracy of impervious surface mapping along urban–rural gradients. Average SUHI intensities were 3.4 °C in Wuhan and 3.3 °C in Brasília, with statistically significant warming trends of 0.04 °C/year and 0.01 °C/year, respectively. Maximum temperature proved to be a robust indicator of SUHI intensification, capturing long-term upward trends. Our findings highlight the important role of urban land cover dynamics in shaping temporal SUHI variability and hotspot emergence. This prototype framework demonstrates the scientific and policy value of combining long-term land cover monitoring information with satellite thermal monitoring to quantify and track SUHI at city scale, supporting sustainable urban planning and climate adaptation strategies.

Remote Sensing

The United States Magnetotelluric Array and the National Impedance Map

The United States Magnetotelluric Array (USMTArray) data set, collected in the years 2006–2024, consists of more than 1,700 long-period magnetotelluric stations covering the entirety of the contiguous United States on a quasi-regular 70 km grid. Funding across multiple federal agencies was critical to sustaining this effort to its completion. Important components of the project included active guidance and participation from the MT community, the open and timely availability of all data, and the application of consistent instrumentation and robust data processing. Together with parallel advancement in the development of publicly available three-dimensional (3D) inversion codes, the USMTArray has revitalized the US magnetotelluric community and increased the visibility of magnetotellurics within the Earth-science community. Taken as a whole, these data are visualized as the National Impedance Map, which, together with a 3D synthesis conductivity model of the nation, reveals the electrical architecture of the contiguous US. USMTArray data are used by researchers worldwide for fundamental and applied studies, including investigations of continental architecture and evolution, estimation of hazards to critical infrastructure due to geomagnetic storms, and assessment of the nation's undiscovered geothermal and mineral resources. We here review the history and development of the project, discuss the challenges and successes in its execution, present the National Impedance Map and synthesis conductivity model, and highlight the breadth of research stemming from this rich data set.

conterminous United States

Is satellite-derived bathymetry vertical accuracy dependent on satellite mission and processing method?

This research focusses on three satellite-derived bathymetry methods and optical satellite instruments: (1) a stereo photogrammetry bathymetry module (SaTSeaD) developed for the NASA Ames stereo pipeline open-source software (version 3.6.0) using stereo WorldView data; (2) physics-based radiative transfer equations (PBSDB) using Landsat data; and (3) a modified composite band-ratio method for Sentinel-2 (SatBathy) with an initial simplified calibration, followed by a more rigorous linear regression against in situ bathymetry data. All methods were tested in three different areas with different geological and environmental conditions, Cabo Rojo, Puerto Rico; Key West, Florida; and Cocos Lagoon and Achang Flat Reef Preserve, Guam. It is demonstrated that all satellite derived bathymetry (SDB) methods have increased accuracy when the results are aligned with higher-accuracy ICESat-2 ATL24 track bathymetry data using the iterative closest point (ICP). SDB vertical accuracy depends more on location characteristics than the method or optical satellite instrument used. All error metrics considered (mean absolute error, median absolute deviation, and root mean square error) can be less than 5% of the maximum bathymetry depth penetration for at least one method, although not necessarily for the same method for all sites. The SDB error distribution tends to be bimodal irrespective of method, satellite instrument, alignment, site, or maximum bathymetry depth, leading to the potential ineffectiveness of traditional error metrics, such as the root mean square error. However, our analysis demonstrates that performing detrending where possible can achieve an error distribution as close to normality as possible for which error metrics are more diagnostic.

Florida

Coastal barrier resilience and resistance: Analysis and metrics for characterizing coastal state

Barrier islands are shaped by a variety of short- and long-term environmental processes such as storms and relative sea-level rise. These islands, found along the estuarine-marine interface, provide ecosystem services including storm surge and wave attenuation, erosion protection to inland marshes, habitat for fish and wildlife, and recreation. Natural resource managers require actionable information on how barrier island resilience and resistance changes over time to understand how an island’s current state relates to past conditions and to inform restoration prioritization and implementation. The U.S. Geological Survey and The Water Institute collaborated on a study to develop indicators of resilience and resistance for barrier islands in Louisiana. Here, resilience captures island persistence on yearly to decadal time scales, and resistance captures persistence on event time scales of days to weeks. The indicators fall in two categories: Tier 1 Screening Metrics, that can be readily calculated from available data, are easily interpretable as an evaluation of barrier condition, and provide a high-level snapshot of overall barrier resilience and resistance; and Tier 2 Analysis Metrics, which are detailed metrics that required specialized analysis and interpretation and are more applicable to answering specific questions managers may have about barrier state. The research team derived Tier 1 resilience indicators from subaerial land and vegetation cover calculated from publicly available maps and products based on satellite imagery. By benchmarking the total land and vegetation extent against their respective historical maxima, this metric provides a snapshot of an island’s current state in the context of its long-term trajectory. The research team developed Tier 1 resistance indicators based on subaerial island configuration and water level recurrence as a proxy for evaluating island resistance to storms, which are the primary driver of short-term change. These Tier 1 metrics can be analyzed over time to provide a high-level assessment of how an island’s resistance decreases because of elevation loss or sea-level rise or increases due to restoration or natural recovery. The research team developed Tier 2 resilience and resistance indicators and associated analyses to provide detailed information for specific time periods or applications (e.g., wildlife management). These metrics include habitat coverage from high-resolution maps, which show composition changes over time to capture the evolving resilience of specific habitat types; high tide flooding analysis, which evaluate island area relative to specified flooding thresholds to characterize resistance in the short-term or, if analyzed over time, indicate changes in resilience; and hypsometric curve analysis, which allows managers to evaluate island area changes above their own elevation benchmarks of interest and similarly characterize resistance in the short-term or indicate changes in resilience if assessed over time. The research team calculated Tier 1 metrics of the barrier islands and headlands along the coast of Louisiana for the period of 1984 through 2021 and Tier 2 metrics for select times during that period depending on data available and quality. The results were captured in a report card for each barrier, which also includes an overview of the metrics and their interpretation; a restoration and storm history; and Tier 1 and Tier 2 metric analysis, including benchmarking against coastwide and regional values as well as to an island’s pre-restoration trajectory. These report cards provide a readily digestible synthesis of barrier condition and trajectory that coastal managers can use to support restoration prioritization and other decisions.

Louisiana

The digital archivist: Automating legacy macroseismic data processing using large language models

Macroseismic data are a key resource to investigate shaking and damage from preinstrumental and early instrumental eras. However, data are often stored as inconsistently formatted reports describing observed shaking and damage, making manually parsing and interpreting accounts labor‐intensive. We introduce a novel workflow using Google’s Gemini 2.5 Pro large language model (LLM) to automate the extraction and structuring of macroseismic observations from summary reports. We apply this workflow to the 22 March 1957 M 5.3 Daly City, California, earthquake as a case study. We used Gemini to extract addresses, originally assigned modified Mercalli intensity values, and descriptions from each report. To address coordinate precision limits, addresses were geocoded via Google’s Geocoding application programming interface. This workflow yielded over 2300 geocoded intensity reports for the Daly City earthquake. We use the geocoded accounts, with the original report intensity assignments, to develop a shaking intensity map that in some respects rivals modern Did You Feel It? Maps. We also extract and present data for the 9 February 1971 M L 6.7 Sylmar, California, earthquake. Our results demonstrate the potential of LLMs for reliably extracting and analyzing large, unstructured macroseismic datasets. LLMs offer a scalable solution for rapidly digitizing macroseismic archives, enabling their broader use to constrain ground‐motion models in modern seismic hazard analysis and to improve our understanding of site effects in urban areas. The concepts explored here may also be applied to the handling of other legacy seismological and earth science data.

Seismological Research Letters

Black rails in Baja California

Summarizing records from 1905 to 2025, we document the presence and distribution of the California black rail ( Laterallus jamaicensis coturniculus ) in northwestern México, particularly Baja California and the Colorado River Delta. This subspecies has a restricted distribution in the western U.S. and northwestern México. We found few records over the past century: sparse detections in the early 1900s and an increase in reported records after 2000. Over 120 years, we compiled 35 documented records of California black rail occurrence in Baja California with a minimum reported count of 56 rails. Our call-broadcast survey methods reconfirmed previously occupied sites and documented the species at a previously unreported site. Surveys in the Baja California portion of the Colorado River Delta yielded 20 detections across nine survey events between 2000 and 2022. In April 2003, standardized surveys detected 12 California black rails: 7 in Bahía de San Quintín, 3 in Arroyo San Telmo, and 2 in Arroyo El Rosario. Our recent survey work (2022–2025) recorded maximum monthly counts of 31 detections at Bahía de San Quintín and 15 detections at Estero de Punta Banda, the latter representing a previously undocumented location for the subspecies. These surveys also yielded the first photographic and acoustic documentation of California black rail in México. The contribution of spatial and temporal data provided by citizen science platforms increased our understanding of the subspecies’ distribution. Enforceable protection of this subspecies’ habitat is needed to safeguard its persistence.

Baja California

U.S.-Mexico Borderland & vegetation community map

People on both sides of the United States-Mexico border need a high-resolution, binational vegetation community map that spans the entire United States-Mexico borderlands. Traditionally, mapping efforts in this region were impeded by complex logistics related to the international border, differing national needs and plans, and resource allocations and priorities. To address this need, scientists from the U.S. Geological Survey (USGS) Southwest Biological Science Center partnered with the Sonoran Joint Venture, the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program, data engineers from the Department of Biosystems Engineering at the University of Arizona, and collaborators from the Wildlands Network, the Borderlands Program to produce the first prototype land cover map within the overlapping Mojave Desert, Sonoran Desert, and the North American Bird Conservation Initiative’s Bird Conservation Region 33 (BCR33) using Landsat satellite data . BCR33 is an area of high biodiversity, providing habitat for bird species of concern and other wildlife. The land cover map supports FWS recovery plan efforts related to conservation planning activities for many species, including Yellow-billed Cuckoo ( Coccyzus americanus ), Cactus Ferruginous Pygmy-Owl ( Glaucidium brasilianum cactorum ), Southwestern Willow Flycatcher ( Empidonax traillii extimus ), Yuma Ridgway’s Rail ( Rallus obsoletus yumanensis ), Bendire’s thrasher ( Toxostoma bendirei ), LeConte’s thrasher ( Toxostoma lecontei ), Masked Bobwhite ( Colinus virginianus ridgwayi ), jaguar ( Panthera onca ), and endangered plants such as Bartram’s stonecrop ( Graptopetalum bartramii ) and the Pima pineapple cactus ( Coryphantha robustispina ssp. robustispina ). In 2024, a Phase-II map for the full BCR33 region was completed, increasing the understanding of the binational nature of natural communities. The published map and associated paper can be found here .

Borderland

Diverging mineral chemistry of iron and nickel throughout Earth’s changing redox conditions reveals foundation for their evolution as protein cofactors

Iron (Fe) and nickel (Ni) were both foundational to early metabolism, yet their biological trajectories diverged as Earth’s surface redox state changed. Here, we integrate mineral chemistry network analysis, protein metal-site coordination-sphere analysis, and curated redox comparisons to test how geochemistry and metalloprotein architecture co-evolved. Mineral network analyses show broader electronegativity variation and network diversity for Fe-bearing minerals through time relative to Ni-bearing minerals. In structural analyses of protein metal centers in a combined Fe/Ni protein structure set, it is shown that Fe- and Ni-associated environments differ in amino-acid composition, hydropathy structure, and cysteine representation. The greater chemical diversity and electronegativity variation in Fe minerals mirror the higher redox and structural versatility of Fe-binding proteins. The presence of Fe in a broader range of mineral and protein environments demonstrates the chemical adaptability of the metal, from the anoxic Archean to oxidative Earth surface conditions following the Great Oxidation Event. Iron, with its broad redox potential range in Fe-oxidoreductases, has a central role in both anaerobic and aerobic metabolisms. Nickel, by contrast, is less widespread in biology. Today, Ni is predominantly employed in deeply branching anaerobic pathways and by proteins with narrower redox potential ranges. Our results show that evolutionary processes, constrained by metal chemistry, habitually utilize Fe as a redox generalist while retaining Ni in specialized roles. The divergent paths of Ni and Fe, from rocks to proteins, demonstrate the intimate relationship between planetary geochemistry and metabolic origins on Earth and suggest that Fe/Ni geochemistry may inform habitability assessments in extraterrestrial environments when interpreted within specific planetary environmental contexts.

Life

Streams, springs, and volcanic lakes for volcano monitoring

Introduction Volcanic unrest can trigger appreciable change to surface waters such as streams, springs, and volcanic lakes. Magma degassing produces gases and soluble salts that are absorbed into groundwater that feeds streams and lakes. As magma ascends, the amount of heat and degassing will increase, and so will any related geochemical and thermal signal. Subsurface magma movement can cause pressurization that alters hydrostatic head and may induce groundwater discharge. Fluid-pressure changes have been linked to distal volcano-tectonic earthquakes (White and McCausland, 2016; Coulon and others, 2017) and phreatic eruptions (for example, Yamaoka and others, 2016). Clearly, changes in groundwater and surface waters are both indicators of unrest and clues to how and where magma is rising toward the surface. Where possible, it is prudent to incorporate real-time hydrologic data into multiparameter monitoring of restless volcanoes. Hydrologic dynamics can also be tracked by changes in groundwater levels that are commonly measured in shallow boreholes (see of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–K, 5 p., https://doi.org/10.3133/sir20245062k. ">chapter K , this volume, on boreholes; Hurwitz and Lowenstern, 2024). Although inferred to be common, relatively few volcano-hydrology anomalies are well documented, and many are essentially anecdotal (Newhall and others, 2001), reflecting the fact that high-resolution time series remain rare. Extreme examples include the 2008 eruption of Nevado del Huila, Colombia, where relatively minor phreatomagmatic eruptions were accompanied by expulsion of as much as 300 million cubic meters of groundwater from fissures high on the volcano (Worni and others, 2011), generating large lahars. Substantial decreases in flow rate from springs about 8 kilometers from the summit of Mayon Volcano, Philippines, have been noted before most eruptions in the 20th century (Newhall and others, 2001). Stream monitoring at Redoubt Volcano in 2009 allowed Werner and others (2012) to recognize that groundwater was unable to absorb (or scrub) the high flux of volcanic gas and that a high CO 2 /SO 2 precursor signal had been evident for 5 months prior to the eruption. A key to better interpreting hydrologic anomalies—or even identifying them—is therefore obtaining adequate baseline data. Most hydrologic monitoring at U.S. volcanoes has been accomplished by intermittent sampling surveys with annual or less frequent sampling (for example, https://hotspringchem.wr.usgs.gov/index.php ). More frequent sampling, however, generally is needed to establish reliable baselines. A recent hydrologic and hydrothermal monitoring experiment at 25 sites and 10 of the 12 level 4 (very high threat) volcanoes in the U.S. portion of the Cascade Range demonstrated that there is sufficient temporal variability in hydrothermal fluxes, even during quiescent periods, that one-time measurements will commonly have limited interpretive value (Crankshaw and others, 2018). Thus, surveys are best augmented with data from streamgages (for example, Evans and others, 2004; Bergfeld and others, 2008). Streamflow (water discharge) data allow measured temperature and specific conductance to be converted to heat and solute mass fluxes, which could be insightful parameters for detecting anomalous activity (McCleskey and others, 2012). At the Yellowstone Caldera, long-term monitoring of river solutes has allowed calculation of the chloride flux, a proxy for heat discharge (Hurwitz and others, 2007; McCleskey and others, 2016) from the subsurface magma. This is readily accomplished because data from streamgages are continuously recorded and archived by the U.S. Geological Survey (USGS) National Water Information System (NWIS) (USGS, 2024). Similar studies on stratovolcanoes or shield volcanoes would be scientifically useful, and yet are logistically challenging, requiring streamgages on numerous radial drainages complemented by either frequent manual sampling or numerous deployments of equipment to measure water temperature and specific conductance as a proxy for water chemistry. Another challenge is that some volcanic areas, especially shield volcanoes, are characterized by near-surface porous rocks and soils, such that surface streams are rare and replaced by distant, dilute large-volume springs with only a trace of any original volcanically sourced water (Manga, 2001; Hurwitz and others, 2021). Volcanic lakes are worthy of special attention for monitoring efforts, as their temperature and composition can provide evidence of increased flux of volatile-rich fluids from below. Quantifying changes in volatile and heat release from magma can be simpler in lakes than for volcanoes with radial drainages and no major lakes. Moreover, volcanic lakes pose a range of hazards themselves, including phreatomagmatic eruptions, debris flows, flank collapse, tsunamis, and toxic gas release (Mastin and Witter, 2000; Delmelle and others, 2015; Manville, 2015; Rouwet and others, 2015)—hazards that have historically been responsible for substantial loss of life at many volcanoes worldwide (Manville, 2015). Catastrophic CO 2 release at Lake Nyos, Cameroon, in 1986 suffocated about 1,750 people and about 3,500 livestock and was probably triggered by a large landslide into the gas-saturated lake (Kling and others, 1987; Evans and others, 1993). Gas-charged springs in Soda Bay within Clear Lake (California) have caused almost a dozen deaths to bathers in the past hundred years (ABC News, 2000). A 2005 example of lake overturn and abundant gas release was documented at Mount Chiginagak in Alaska (Schaefer and others, 2008) but did not result in any human casualties. Although thermally stratified lakes, which promote trapping of exsolved magmatic gas, tend to develop in tropical regions, the phenomenon can also arise where salinity creates meromixis (a condition in which a lake does not mix completely), as occurs in Mono Lake, California (Jellison and Melack, 1993; Jellison and others, 1998). If magma erupts or flows into a lake, the interaction between hot magma and cold water can be explosive (Mastin and others, 2004; Zimanowski and others, 2015) and substantially expand the area affected by the eruption. Another hazard is the breaching of crater rims by landslides triggered by volcanic and (or) seismic activity. Under some circumstances, substantial volumes of water can be displaced, leading to large floods and lahars. Late Holocene lake flooding from Aniakchak Crater in the Alaska Peninsula (Waythomas, 2022) and from Paulina Lake in Newberry Crater, Oregon (Chitwood and Jensen, 2000), caused by the failure of outlet sills, testify to the substantial hazards at lake-filled calderas. Several volcanic systems in the United States host lakes known to receive heat and gas from underlying magma. These lakes vary widely in area, depth, and chemical composition. Lakes are present at level 4 volcanoes, including Crater Lake and Newberry Volcano in Oregon; Yellowstone Caldera in Wyoming; Long Valley Caldera, Clear Lake volcanic field, Medicine Lake, and Salton Buttes in California; and Aniakchak Crater, Mount Katmai, Fisher Caldera, Mount Okmok, and Kaguyak Crater, among others, in Alaska. A water lake was present in Halemaʻumaʻu, the crater of Kīlauea, Hawai‘i (fig. F1), from October 2019 to December 2020. Level 3 volcanoes with lakes include Mono Lake volcanic field (Calif.), Mount Bachelor (Ore.), Ukinrek Maars and Mount Chiginagak (Alaska), and Soda Lake (Nevada). In addition, there are lakes at many levels 1 and 2 volcanoes. In the United States, there are no strongly acidic lakes that receive abundant input of magmatic gas, such as those found at Mount Ruapehu (New Zealand), Ijen and Kelud (Indonesia), and Poás (Costa Rica). Nevertheless, many contain fluids that provide clues to magmatic processes below. Since publication of a previous report on recommended instrumentation for volcano monitoring (Moran and others, 2008), continuous hydrologic monitoring has become increasingly feasible. However, changes in water pressure, temperature, and chemistry remain, in general, poorly studied phenomena at volcanoes (Sparks, 2003; National Academies of Sciences, Engineering, and Medicine, 2017). Recent efforts by the USGS have included the temporary study of Cascade Range volcanoes, which included frequent (15 minute to hourly) temporal sampling of temperature, depth, and conductivity (Crankshaw and others, 2018; Ingebritsen and Evans, 2019). At Yellowstone Caldera, many streamgages have now added thermistors and specific conductance sensors, allowing estimation of time-dependent chloride flux as a proxy for variations in subsurface heat flux (McCleskey and others, 2012, 2016). Efforts to better understand lakes have also accelerated, with bathymetric mapping and sampling carried out at several locations in the United States. Especially thorough work was done at Yellowstone Lake thanks to the Hydrothermal Dynamics of Yellowstone Lake (HD-YLAKE, https://hdylake.org ) project, funded primarily by the National Science Foundation. In addition to geophysical surveys and recovery of cores and other samples, HD-YLAKE investigations included remotely operated vehicle (ROV) investigations of hydrothermal vents on the lake floor (fig. F2). Data collected by the ROV provided a better understanding of the thermal and chemical influx from lake-bottom hydrothermal systems (Sohn and others, 2017). In this chapter, we focus on detecting changes in the chemistry, temperature, discharge, or water levels of streams, springs, and lakes that can be caused by seismicity, volumetric strains, or increases in gas flux associated with ascending magma. There is unavoidable overlap with other chapters of this report. Samples of water and gas can also be obtained in boreholes ( of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–K, 5 p., https://doi.org/10.3133/sir20245062k. ">chapter K , this volume; Hurwitz and Lowenstern, 2024), both shallow and deep. Gas monitoring ( of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–E, 11 p., https://doi.org/10.3133/sir20245062e.">chapter E , this volume; Lewicki and others, 2024) relies in part on samples from springs and wells, particularly where measurable gas plumes are absent. Water acts as a trigger and lubricant for landslides and sediment-rich floods, and so hydrology has obvious relevance for lahar monitoring, as discussed in of Flinders, A.F., Lowenstern, J.B., Coombs, M.L., and Poland, M.P., eds., Recommended capabilities and instrumentation for volcano monitoring in the United States: U.S. Geological Survey Scientific Investigations Report 2024–5062–H, 6 p., https://doi.org/10.3133/sir20245062h. ">chapter H (this volume; Thelen and others, 2024). Shared situational awareness among scientists engaged in geophysical, gas, and hydrologic monitoring will improve overall understanding of the volcanic hazard.

Scientific Investigations Report

Earthquake rupture arrest from depth‐dependent frictional stability on the Pütürge segment of the East Anatolian Fault Zone, Türkiye (Turkey)

Determining why earthquake ruptures stop is a central challenge in earthquake science and seismic hazard assessment. The Pütürge segment of the East Anatolian Fault Zone, Türkiye, exhibits shallow creep (<∼3 km depth) yet hosts M > 6.5 earthquake ruptures at greater depth. Here, we evaluate whether variations in frictional stability along this segment aided arrest of the 2020 M 6.7 Elaziğ and 2023 M 7.8 Pazarcık earthquake ruptures. Analysis of Sentinel‐1 Synthetic Aperture Radar imagery indicates the 2023 M 7.8 rupture propagated laterally into a metamorphic massif within the Pütürge segment, where slip rapidly decayed below detection limits. Creepmeters along this segment recorded no significant surface afterslip (<3 mm) in the following year. To investigate this fault‐slip behavior, we conducted triaxial friction experiments on Pütürge fault gouge sampled from an outcrop exposure. The gouge, composed primarily of muscovite, quartz, and calcite, is velocity strengthening at conditions approximating 0–2.5 km depth and velocity weakening at 4–5 km depth. This transition to velocity‐weakening friction is associated with enhanced comminution and shear localization observed microstructurally. Our results suggest that depth‐dependent frictional stability of the Pütürge fault segment facilitates rupture nucleation and propagation at depth while maintaining rupture‐arresting behavior near Earth’s surface.

Pütürge segment of the East Anatolian Fault Zone

The 3D Elevation Program—Supporting Rhode Island’s economy

Introduction High-resolution elevation data are critical to applications of landscape modeling and planning, both of which have a significant effect on Rhode Island’s economy. In these and other enterprises, program managers, while aiming to strike a balance between accuracy and cost, strive to obtain the best available elevation data to help them address a range of issues. Programs focused on climate change, environmental management, transportation design and asset management, aviation navigation and safety, riverine ecosystem management, wildlife habitat characterization and management, shellfish aquaculture, and the management and mapping of forests, parks and recreation areas, soils, wetlands, and impervious surfaces are also among the critical applications that meet the State’s management needs and depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features. The 3D Elevation Program (3DEP) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at quality level 2 or better to meet the many needs of the Nation and Rhode Island. The status of available and in-progress 3DEP baseline lidar data in Rhode Island is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 ( https://www.usgs.gov/3dep/lidarspec ) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $178,560 in new benefits annually to the State. The top 10 Rhode Island business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.

Rhode Island

Long-term communication of aftershock forecasts: The Canterbury earthquake sequence in New Zealand

On 14 February 2016, a magnitude (M)5.7 earthquake struck in Christchurch New Zealand (Aotearoa in the Maori language). The shaking caused damage to historic facades, power outages, cliff collapses, rock falls, and liquefaction but no reported injuries or fatalities. This Valentine’s Day earthquake was an aftershock in the Canterbury earthquake sequence (CES), which began on 4 September 2010 with the M7.1 Darfield Earthquake and included the destructive and fatal M6.2 Christchurch aftershock on 22 February 2011. This study, eight months after the Valentine’s Day earthquake and six years after the initiation of the CES, is the first to explore long-term aftershock forecast information and communication needs. The exploratory study also aimed to gather feedback on aftershock scenarios, an alternative form for communicating the forecast. The qualitative study involved workshops with emergency managers, public health officials, and members of the public in Christchurch. Key findings for long-term communication throughout an earthquake sequence include: 1. divergent earthquake experiences affect aftershock communication response and information needs; 2. understanding aftershock sequence behavior is foundational to sense-making when large aftershocks occur; 3. strategic earthquake sequence updates from the trusted science agency and local agencies could serve as important reminders for earthquake preparedness; 4. communication of aftershock forecast uncertainty could aid with both the credibility of the information and living with uncertainty, and 5. inclusion of impact information and preparedness advice into aftershock forecast scenarios could provide links to actionable information. The paper derives implications for research and practice of long-term communications during an aftershock sequence.

Christchurch

Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning

Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km 2 (0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications.

California